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Found 5 papers, 0 papers with code
Fast Second Order Stochastic Backpropagation for Variational Inference
We propose a second-order (Hessian or Hessian-free) based optimization method for variational inference inspired by Gaussian backpropagation, and argue that quasi-Newton optimization can be developed as well.
Fast Second-Order Stochastic Backpropagation for Variational Inference
We propose a second-order (Hessian or Hessian-free) based optimization method for variational inference inspired by Gaussian backpropagation, and argue that quasi-Newton optimization can be developed as well.
Demixing odors - fast inference in olfaction
Thus, at the behavioral level, the two algorithms make very similar predictions.
Modelling Reciprocating Relationships with Hawkes Processes
We present a Bayesian nonparametric model that discovers implicit social structure from interaction time-series data.
Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models
This ability requires a neural code that represents probability distributions and neural circuits that are capable of implementing the operations of probabilistic inference.
